could not find function "some Function" from some package - r

I am encountering an error when creating a data frame. I was running some package one day back everything was good but now I am having some issues like not able to find some function. I suspect its coz of my R studio (Ver. 1.2.5033). What do you think?
After loading some packages I can't access functions associated with them.
Best:
Imran
require(package)
could not find function "package's function"

Related

I cannot obtain scores for a metaMDS object in RStudio (package: vegan)

I'm using vegan 2.6.4 in RStudio, and have had an unusual error message pop up when I run the the following:
nmds11 = metaMDS(m_com11, distance = "bray")
data.scores11 = as.data.frame(scores(nmds11)$sites)
Error in UseMethod("scores") :
no applicable method for 'scores' applied to an object of class "c('metaMDS', 'monoMDS')
I can safely say this has never happened to me, and I was using the exact same code on a different dataset 5 minutes ago with no issues. I have also previously run this same script on at least a dozen other matrices with no errors.
I have tried calling scores.metaMDS as suggested when looking up the scores function (to help specify what type of object I'm trying to get scores from), but that function apparently does not exist. I've also tried running some old scripts that always worked in the past, with the same unfortunate results.
Any idea what I can do to address this?
Try using vegan::scores(); it could be that some other package you have loaded also has a scores() generic that is overwriting vegan::scores(). You can also try the much more specific vegan:::scores.metaMDS() if the whole S3 system has gotten clobbered.
Beyond that, restart R (in RStudio, find the Restart R option in the menus) so you get a clean session and try running your code again.
I I tried vegan:::scores.metaMDS() without restarting RStudio and it works ! Thanks !!!

Autospearman in R

Did anyone used the AutoSpearman function from "software-analytics/Rnalytica" package and worked for him? I keep having errors while loading the package. You can find here the documentation of AutoSpearman function.

Exporting function with snowfall

I am currently developing an R package and would like to make use of parallelization with the package snowfall. I'd like to call a function (actually an Rcpp wrapper if this matters) from the package itself, so the function is currently not floating around in the environment.
sfInit(parallel=TRUE,cpus=Cpu)
sfExport("RcppFunction")
sfLapply(1:N,function(cc) RccpFunction(args))
sfStop()
Anytime I try to do this I get the following error message:
Error in sfExport("RcppFunction") :
Unknown/unfound variable RcppFunction in export. (local=TRUE)
I already tried some tutorials and online handbook, but did not found yet the solution how to export any function to snowfall within a package. As far as I see it doesn't really have to do that this particular function is an RcppFunction. I hope someone can help! Thanks in advance!
PS: I already found this post, but I cannot export my own package to snowfall - at least this doesn't make sense to me.

ts_backtesting function from TSstudio is not showing in the list of functions in TSstudio package in R

I have been trying to perform the horse approach for finding the best model to run on the time series data but when I run ts_backtesting function, there is a message in console that
Error in ts_backtesting(x) : could not find function "ts_backtesting"
Can anyone please help me know why I am getting such error and how to avoid that.
I checked the latest version of the package, didn't find this function anymore
https://cran.r-project.org/web/packages/TSstudio/index.html,
instead, a function called 'train_model' can be used to do a similar thing.

R Package Build/Install Error: "object not found" even though I have it in R/sysdata.rda

Similar Question
accessing sysdata.rda within package functions
Why This Similar Question Does Not Apply To Me
They were able to actually build it, and apparently it was a Github error for them (not related)
R VERSION
3.4.2 (I tried using 3.4.3 as well but the same problem occurred)
EDIT: I am on Windows 10
Context
I have fully read the following tutorial on R packages and how to include .Rda files in them. I have LazyData in my DESCRIPTION file set as true as well. I have tried both the data/ folder implementation and the R/sysdata.rda implementation using the function devtools::use_data() with the respective options of internal = FALSE and internal = TRUE.
However, when I try to build the package, or use devtools::install (which builds as well I assume), it fails and gives me the following error message:
Error in predict(finalModel, newInput) : object 'finalModel' not found
Where finalModel is stored within my .rda file.
Does anyone know any possible reasons why this might occur?
I also asked a coworker to install the package on his machine, but unfortunately he got the exact same error.
I made another test package as a 'sanity-check' by creating a simple linear model using the lm() function on datasets::swiss, and then made a test package with this newly created model as a .rda file. When I referenced this test model in a function within this test package, it eerily worked, despite the fact that (to the best of my knowledge) I used the exact same steps to create this new R package.
Also, I unfortunately cannot share the code for the package I am creating, but I am willing to share the code for the test package that uses the swiss dataset.
Thank you in advance.
EDIT: My .rda file I am putting in the package was created last year, if that has anything to do with it.
I just solved a similar issue of having object 'objectName' not found that arose during package management. In my case, the issue related to losing the context of variables when working with parallelization.
When using parallel::clusterExport(cl, varlist=c("function-name")), clusterExport looks at .GlobalEnv for variable definitions. This wouldn't come up during debugging, as I always the variables defined in .GlobalEnv. The solution was to state the environment explicitly: parallel::clusterExport(cl, varlist=c("function-name"), envir=environment()). This ensures that the parallel processes have context of the variables within the data/ folder and R/sysdata.rda.
Source
If you have more than one internal file, you must save them together:
usethis::use_data(file_1,
file_2,
file_3,
internal = TRUE,
overwrite = TRUE)

Resources